在Python多处理库中，是否有支持多个参数的pool.map变体？
import multiprocessing
text = "test"
def harvester(text, case):
X = case[0]
text + str(X)
if __name__ == '__main__':
pool = multiprocessing.Pool(processes=6)
case = RAW_DATASET
pool.map(harvester(text, case), case, 1)
pool.close()
pool.join()
当前回答
import time
from multiprocessing import Pool
def f1(args):
vfirst, vsecond, vthird = args[0] , args[1] , args[2]
print(f'First Param: {vfirst}, Second value: {vsecond} and finally third value is: {vthird}')
pass
if __name__ == '__main__':
p = Pool()
result = p.map(f1, [['Dog','Cat','Mouse']])
p.close()
p.join()
print(result)
其他回答
将Python 3.3+与pool.starmap（）一起使用：
from multiprocessing.dummy import Pool as ThreadPool
def write(i, x):
print(i, "---", x)
a = ["1","2","3"]
b = ["4","5","6"]
pool = ThreadPool(2)
pool.starmap(write, zip(a,b))
pool.close()
pool.join()
结果：
1 --- 4
2 --- 5
3 --- 6
如果您喜欢，还可以zip（）更多参数：zip（a，b，c，d，e）
如果希望将常量值作为参数传递：
import itertools
zip(itertools.repeat(constant), a)
如果您的函数应该返回以下内容：
results = pool.starmap(write, zip(a,b))
这将提供一个包含返回值的列表。
我认为以下内容会更好：
def multi_run_wrapper(args):
return add(*args)
def add(x,y):
return x+y
if __name__ == "__main__":
from multiprocessing import Pool
pool = Pool(4)
results = pool.map(multi_run_wrapper,[(1,2),(2,3),(3,4)])
print results
输出
[3, 5, 7]
如何获取多个参数：
def f1(args):
a, b, c = args[0] , args[1] , args[2]
return a+b+c
if __name__ == "__main__":
import multiprocessing
pool = multiprocessing.Pool(4)
result1 = pool.map(f1, [ [1,2,3] ])
print(result1)
对于Python 2，可以使用此技巧
def fun(a, b):
return a + b
pool = multiprocessing.Pool(processes=6)
b = 233
pool.map(lambda x:fun(x, b), range(1000))
另一个简单的选择是将函数参数包装在元组中，然后包装应该在元组中传递的参数。在处理大量数据时，这可能并不理想。我相信它会为每个元组创建副本。
from multiprocessing import Pool
def f((a,b,c,d)):
print a,b,c,d
return a + b + c +d
if __name__ == '__main__':
p = Pool(10)
data = [(i+0,i+1,i+2,i+3) for i in xrange(10)]
print(p.map(f, data))
p.close()
p.join()
以某种随机顺序给出输出：
0 1 2 3
1 2 3 4
2 3 4 5
3 4 5 6
4 5 6 7
5 6 7 8
7 8 9 10
6 7 8 9
8 9 10 11
9 10 11 12
[6, 10, 14, 18, 22, 26, 30, 34, 38, 42]
